ScanDisk To Release 32GB and 16GB Ultra II SDHC

Giving photo enthusiasts the freedom to take more pictures and shoot more video, SanDisk Corporation today increased both capacities and speeds in its SanDisk Ultra II line with the introduction of 32- and 16-gigabyte (GB) SDHC cards and an 8GB SDHC Plus card.

Ideal for today’s camcorders and point-and-shoot digital cameras that can record both video and still images, the cards offer faster read and write speeds of 15 megabytes per second (15MB/sec), up from previous speeds of 10MB/sec read and 9MB/sec write in the SanDisk Ultra II line.

The 32GB Ultra II SDHC card, which is the industry-leading capacity and will be the highest capacity consumer flash memory card that SanDisk produces, will be able to store more than 8,000 high-resolution pictures or up to 40 hours of video. A SanDisk MicroMate USB 2.0 Reader – a $20 value – is packaged with the 32GB and 16GB cards, giving users a one-stop solution for capturing, storing and transferring their images.

Beyond speed and capacity, the 8GB SanDisk Ultra II SDHC Plus offers both SD and USB functionality in one card. Designed with SanDisk’s unique, patented Hinge Lock technology, the card may be inserted into a USB port on any computer. This two-in-one SD-plus-USB feature eliminates the need to carry cables or card readers to transfer photos and videos from cameras. Despite its small size, the hinge is sturdy – having survived more than 10,000 open-close cycles in SanDisk’s durability testing.

Eye-Fi: Add Wi-Fi To Digital  Camera

                                       The Eye-Fi is an Wireless SD memory card that adds Wi-Fi to any camera that supports SD memory card. It can automatically upload pictures from your digital camera to your PC or Mac and to your favorite photo sharing, printing, blogging or social networking site.

The Eye-Fi is like any other SD card, except that there is some setup to do first. Once that is all done, the point of the Eye-Fi is to upload your photos while your camera is on and connected your wireless network to one of the many supported photo sharing services and/or your computer. It appears as though Eye-Fi is aiming to make repetitive card readings and fiddling with a USB cable things of the past.

Setting up the Eye-Fi is fairly simple but involves installing local software on your Mac/PC (no Linux support) which receives settings from an Eye.fi account you must create. The first step is plugging the Eye-Fi with its included SD card reader into your computer. From there, you find the appropriate installer for your OS then install and run it.

Check this excellent review & step by step installation process.

Eye-Fi supports many of the photo sharing services like Fotki, Sharpcast, Flickr, Picasa Web Albums, Webshots, dotPhoto, Photobucket, Facebook, SmugMug, Vox, Walmart, Snapfish, Shutterfly, Phanfare, Kodak Gallery, TypePad and Gallery 2.

Eye-Fi: Add Wi-Fi To Digital  Camera

                                       The Eye-Fi is an Wireless SD memory card that adds Wi-Fi to any camera that supports SD memory card. It can automatically upload pictures from your digital camera to your PC or Mac and to your favorite photo sharing, printing, blogging or social networking site.

The Eye-Fi is like any other SD card, except that there is some setup to do first. Once that is all done, the point of the Eye-Fi is to upload your photos while your camera is on and connected your wireless network to one of the many supported photo sharing services and/or your computer. It appears as though Eye-Fi is aiming to make repetitive card readings and fiddling with a USB cable things of the past.

Setting up the Eye-Fi is fairly simple but involves installing local software on your Mac/PC (no Linux support) which receives settings from an Eye.fi account you must create. The first step is plugging the Eye-Fi with its included SD card reader into your computer. From there, you find the appropriate installer for your OS then install and run it.

Check this excellent review & step by step installation process.

Eye-Fi supports many of the photo sharing services like Fotki, Sharpcast, Flickr, Picasa Web Albums, Webshots, dotPhoto, Photobucket, Facebook, SmugMug, Vox, Walmart, Snapfish, Shutterfly, Phanfare, Kodak Gallery, TypePad and Gallery 2.

Light To Replace Copper Wires In Computers

Scientists at IBM recently completed research which may soon result in supercomputers the size of current notebooks.

This would be achieved by replacing existing copper wires used to couple processing cores together with a silicon Mach-Zehnder electro-optic modulator, which would allow light to pass the data. The connector created by the team uses light to pass data between the computational cores that is faster and uses less power than copper wires.

With light the researchers, led by Dr Will Green, can cut the amount of power needed to move data between processors and slash the amount of heat a large computational cluster produces.

The technology, which can transfer data up to a distance of a few centimetres, is about 100 times faster than wires and consumes one-tenth as much power, said Dr Green.

So the lower power requirement should reduce operational costs for supercomputers.

“What we have done is a significant step toward building a vastly smaller and more power-efficient way to connect those cores, in a way nobody has done before,” said Dr Tze-chiang Chen, a spokesman for IBM’s science and technology research division.

But this technology is still in labs, so it would take few years to see this technology in the market.

Supercomputer Performs Laser Cancer Surgery

Lonestar, a supercomputer at the Texas Advanced Computing Center (TACC) recentlyperformed a laser cancer surgery on a dog without the intervention of a surgeon. The operation was done in Houston without the intervention of a human surgeon while the Lonestar supercomputer, a Dell Linux Cluster with 5,840 processors, was in Austin.

The treatment was developed collaboratively by computational experts from UT-Austin, cyberinfrastructure specialists and systems from TACC, and leading technologists from the M.D. Anderson Cancer Center in Houston. Using precise lasers, state-of-the-art thermal imaging technology, and advanced computational methods, dynamic, data-driven treatments are being pursued as a minimally invasive alternative to the standard treatment of cancer.

The procedure was the culmination of three years of research and development into the algorithms, computer codes, imaging technology, and cyberinfrastructure that would allow a supercomputer in Austin to perform a minimally invasive laser treatment on a canine in Houston, without the intervention of a surgeon. The scientists took a collective breath.

“We had a fifteen minute window in which a million things had to go right for this treatment to be successful,” explained David Fuentes, a post-doctoral student at The University of Texas at Austin’s Institute for Computational Engineering and Sciences (ICES), and the central developer of the project. “There had to be no flaw, no silly bug, everything had to go perfectly. And if that wasn’t complicated enough, you add the complexity of a living animal. This is a pretty formidable problem.”

The technology is just in the early experimental stage, but it looks promising. It’s a long process before these protocols are made robust and have wide-spread use in human subjects. But this is a step along a path that will be followed.

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Google Builds Artificial Brain Which Can Recognize A Cat

The Google X laboratory has invented some pretty cool stuff: refrigerators that can order groceries when your food runs low, elevators that can perhaps reach outer space, self-driving cars. So it’s no surprise that their most recent design is the most advanced, highest functioning, most awesome invention ever… a computer that likes watching YouTube cats?

Okay, it’s a bit more advanced than that. Several years ago, Google scientists began creating a neural network for machine learning. The technique Google X employed for this project is called the “deep learning,” a method defined by its massive scale. In layman’s terms, they connected 16,000 computer processors and let the network they created roam free on the Internet so as to simulate a human brain learning.

Stanford University computer scientist Andrew Y. Ng, led the Google team in feeding the neural network 10 million random digital images from YouTube videos. The machine was not “supervised,” i.e. it was not told what a cat is or what features a cat has; it simply looked at the data randomly fed to it. Ng found that there was a small part of the computer’s “brain” that taught itself to recognize felines. “It basically invented the concept of a cat,” Google fellow Jeff Dean told the New York Times.

So Google may have created a machine that can teach itself. But what Ng and his team have done is not as new as you may think. Over the years, as the scale of software simulations has grown, machine learning systems have advanced; last year, Microsoft scientists suggested that the “deep learning” technique could be used to build computer systems to understand human speech. This Google X machine is the cream of the crop—twice as accurate as any other machine before it. However, “it is worth noting that our network is still tiny compared to the human visual cortex,” the researchers wrote, “which is a million times larger in terms of the number of neurons and synapses.”

After “viewing” random pictures from random YouTube videos, the neural network created a digital image of a cat based on its “memory” of the shapes it saw in the images. The cat the computer created is not any specific cat, but what the computer imagines to be a cat. Plato had his Forms, and now Google has its computer-generated cat image.

NEW ERA OF INVERTERS

NEW ERA OF INVERTERS 

ABSTRACT:-

 Multilevel inverters are very useful compare to the two-level inverter because of its use of low rating devices and less EMI problem and also less dv/dt. But conventional multilevel inverters are generally avoided in industry because of its complexity. The power circuit proposed in this work is the simplest of all the existing five-level inverter but still it is capable of performing same as the others. 

     Asymmetrical pole voltage produces the unwanted common-mode voltage in the induction motor drive system. Common-mode voltage elimination is necessary in the induction motor drives because this alternating common mode voltage produce leakage current that will flow through the rotor and produce erosion in the rotor body and also produce motor failure. So elimination of common mode voltage is very necessary. This circuit is capable of eliminating the common-mode voltage. 

     A five level inverter requires four voltage sources, but here the circuit is reduced by reducing the number of the DC voltage sources. Here two DC voltage sources are used which are divided by four parts by the four DC-link capacitors, but unbalance may occur in the capacitor voltages. The controller used in this proposed method is capable of balance the DC-link capacitor voltages if unbalancing occur.
             This paper presents Ability to reduce the voltage stress on each power device due to the utilization of multiple levels on the DC bus.   Important when a high DC side voltage is imposed by an application (e.g. traction systems).  Even at low switching frequencies, smaller distortion in the multilevel inverter AC side waveform can be achieved.
     
     The main multilevel inverter circuit topologies are
1.    Diode-clamped Multilevel Inverter
2.    Imbricated Cell Multilevel Inverter
3.    Modular Structured Multilevel Inverter